The effects of energy metabolism variables on feed efficiency in respiration chamber studies with lactating dairy cows

The objective of the present study was to investigate factors related to variation in feed efficiency (FE) among cows. Data included 841 cow/period observations from 31 energy metabolism studies assembled across 3 research stations. The cows were categorized into low-, medium-, and high-FE groups according to residual feed intake (RFI), residual energy-corrected milk (RECM), and feed conversion efficiency (FCE). Mixed model regression was conducted to identify differences among the efficiency groups in animal and energy metabolism traits. Partial regression coefficients of both RFI and RECM agreed with published energy requirements more closely than cofficients derived from production experiments. Within RFI groups, efficient (Low-RFI) cows ate less, had a higher digestibility, produced less methane (CH4) and heat, and had a higher efficiency of metabolizable energy (ME) utilization for milk production. High-RECM (most efficient) cows produced 6.0 kg/d more of energy-corrected milk (ECM) than their Low-RECM (least efficient) contemporaries at the same feed intake. They had a higher digestibility, produced less CH4 and heat, and had a higher efficiency of ME utilization for milk production. The contributions of improved digestibility, reduced CH4, and reduced urinary energy losses to increased ME intake at the same feed intake were 84, 12, and 4%, respectively. For both RFI and RECM analysis, increased metabolizability contributed to approximately 35% improved FE, with the remaining 65% attributed to the greater efficiency of utilization of ME. The analysis within RECM groups suggested that the difference in ME utilization was mainly due to the higher maintenance requirement of Low-RECM cows compared with Medium- and High-RECM cows, whereas the difference between Medium- and High-RECM cows resulted mainly from the higher efficiency of ME utilization for milk production in High-RECM cows. The main difference within FCE (ECM/DMI) categories was a greater (8.2 kg/d) ECM yield at the expense of mobilization in High-FCE cows compared with Low-FCE cows. Methane intensity (CH4/ECM) was lower for efficient cows than for inefficient cows. The results indicated that RFI and RECM are different traits. We concluded that there is considerable variation in FE among cows that is not related to dilution of maintenance requirement or nutrient partitioning. Improving FE is a sustainable approach to reduce CH4 production per unit of product, and at the same time improve the economics of milk production.202

Between-cow variation in the components of feed efficiency

A meta-analysis based on an individual-cow data set was conducted to investigate between-cow variations in the components and measurements of feed efficiency (FE) and to explore the associations among these components. Data were taken from 31 chamber studies, consisting of a total of 841 cow/period observations. The experimental diets were based on grass or corn silages, fresh grass, or a mixture of fresh grass and straw, with cereal grains or by-products as energy supplements, and soybean or canola meal as protein supplements. The average forage-to-concentrate ratio across all diets on a dry matter basis was 56:44. Variance component and repeatability estimates of FE measurements and components were determined using diet, period, and cow within experiment as random effects in mixed procedures of SAS (SAS Institute Inc., Cary, NC). The between-cow coefficient of variation (CV) in gross energy intake (GE; CV = 0.10) and milk energy (El) output as a proportion of GE (El/GE; CV = 0.084) were the largest among all component traits. Similarly, the highest repeatability estimates (≥0.50) were observed for these 2 components. However, the between-cow CV in digestibility (DE/GE), metabolizability [metabolizable energy (ME)/GE], methane yield (CH4E/GE), proportional urinary energy output (UE/GE), and heat production (HP/GE), as well as the efficiency of ME use for lactation (kl), were rather small. The least repeatable component of FE was UE/GE. For FE measurements, the between-cow CV in residual energy-corrected milk (RECM) was larger than for residual feed intake (RFI), suggesting a greater possibility for genetic gain in RECM than in RFI. A high DE/GE was associated with increased CH4E/GE (r = 0.24), HP/GE (r = 0.12), ME/GE (r = 0. 91), energy balance as a proportion of GE (EB/GE; r = 0.35), and kl (r = 0.10). However, no correlation between DE/GE and GE intake or UE/GE was observed. Increased proportional milk energy adjusted to zero energy balance (El(0)/GE) was associated with increases in DE/GE, ME/GE, EB/GE, and kl but decreases in UE/GE, CH4E/GE, and HP/GE, with no effect on GE intake. In conclusion, several mechanisms are involved in the observed differences in FE among dairy cows, and reducing CH4E yield (CH4E/GE) may inadvertently result in reduced GE digestibility. However, the selection of dairy cows with improved energy utilization efficiencies offers an effective approach to lower enteric CH4 emissions.202

Predicting feed intake and feed efficiency in lactating dairy cows using digesta marker techniques

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Review: In vivo and postmortem effects of feed antioxidants in livestock: A review of the implications on authorization of antioxidant feed additives

The pivotal roles of regulatory jurisdictions in the feed additive sector cannot be over-emphasized. In the European Union (EU), antioxidant substances are authorized as feed additives for prolonging the shelf life of feedstuffs based on their effect for preventing lipid peroxidation. However, the efficacy of antioxidants transcends their functional use as technological additives in animal feeds. Promising research results have revealed the in vivo efficacy of dietary antioxidants for combating oxidative stress in production animals. The in vivo effect of antioxidants is significant for enhancing animal health and welfare. Similarly, postmortem effect of dietary antioxidants has been demonstrated to improve the nutritional, organoleptic and shelf-life qualities of animal products. In practice, dietary antioxidants have been traditionally used by farmers for these benefits in livestock production. However, some antioxidants particularly when supplemented in excess could act as prooxidants and exert detrimental effects on animal well-being and product quality. Presently, there is no exclusive legislation in the EU to justify the authorization of antioxidant products for these in vivo and postmortem efficacy claims. To indicate these efficacy claims and appropriate dosage on product labels, it is important to broaden the authorization status of antioxidants through the appraisal of existing EU legislations on feed additives. Such regulatory review will have major impact on the legislative categorization of antioxidants and the efficacy assessment in the technical dossier application. The present review harnesses the scientific investigations of these efficacy claims in production animals and, proposes potential categorization and appraisal of in vivo methodologies for efficacy assessment of antioxidants. This review further elucidates the implication of such regulatory review on the practical application of antioxidants as feed additives in livestock production. Effecting these regulatory changes will stimulate the innovation of more potent antioxidant products and create potential new markets that will have profound economic impacts on the feed additive industry. Based on the in vivo efficacy claims, antioxidants may have to contend with the legislative controversy of either to be considered as veterinary drugs or feed additives. In this scenario, antioxidants are not intended to diagnose or cure diseases as ascribed to veterinary products. This twisted distinction can be logically debated with reference to the stipulated status of feed additives in Commission Regulation (EC) No 1831/2003. Nonetheless, it is imperative for relevant stakeholders in the feed additive industry to lobby for the review of existing EU legislations for authorization of antioxidants for these efficacy claims.</p

The use of an upgraded GreenFeed system and milk fatty acids to estimate energy balance in early-lactation cows

Measurements of energy balance (EB) require the use of respiration chambers, which are quite expensive and laborious. The GreenFeed (GF) system (C-Lock Inc.) has been developed to offer a less expensive, user friendly alternative. In this study, we used the GF system to estimate the EB of cows in early lactation and compared it with EB predicted from energy requirements for dairy cows in the Finnish feeding standards. We also evaluated the association between milk fatty acids and the GF estimated EB. The cows were fed the same grass silage but supplemented with either cereal grain or fibrous by-product concentrate. Cows were followed from 1 to 18 wk of lactation, and measurements of energy metabolism variables were taken. Data were subjected to ANOVA using the mixed model procedure of SAS (SAS Institute Inc.). The repeatability estimates of the gaseous exchanges from the GF were moderate to high, presenting an opportunity to use it for indirect calorimetry in EB estimates. Energy metabolism variables were not different between cows fed different concentrates. However, cows fed the grain concentrate produced more methane (24.0 MJ/d or 62.9 kJ/MJ of gross energy) from increased digestibility than cows fed the by-product concentrate (21.3 MJ/d or 56.5 kJ/MJ of gross energy). Nitrogen metabolism was also not different between the diets. Milk long-chain fatty acids displayed an inverse time course with EB and de novo fatty acids. There was good concordance (0.85) between EB predicted using energy requirements derived from the Finnish feed table and EB estimated by the GF system. In conclusion, the GF can accurately estimate EB in early-lactating dairy cows. However, more data are needed to further validate the system for a wide range of dietary conditions

Predicting CO2 production of lactating dairy cows from animal, dietary, and production traits using an international dataset

Automated measurements of the ratio of concentrations of methane and carbon dioxide, [CH4]:[CO2], in breath from individual animals (the so-called “Sniffer-technique”) and estimated CO2 production can be used to estimate CH4 production, provided that CO2 production can be reliably calculated. This would allow CH4 production from individual cows to be estimated in large cohorts of cows, whereby ranking of cows according to their CH4 production might become possible and their values could be used for breeding of low CH4 emitting animals. Estimates of CO2 production are typically based on predictions of heat production, which can be calculated from body weight (BW), energy-corrected milk yield, and days of pregnancy. The objectives of the present study were to develop predictions of CO2 production directly from milk production, dietary, and animal variables, and furthermore develop different models to be used for different scenarios, depending on available data. An international dataset with 2,244 records from individual lactating cows including CO2 production and associated traits, as dry matter intake (DMI), diet composition, BW, milk production and composition, days in milk and days pregnant, was compiled to constitute the training dataset. Research location and experiment nested within research location were included as random intercepts. The method of CO2 production measurement (respiration chamber (RC) or GreenFeed (GF)) was confounded with research location, and therefore excluded from the model. In total, 3 models were developed based on the current training dataset: Model 1 (“Best Model”), where all significant traits were included, Model 2 (“On-Farm Model”), where DMI was excluded, and Model 3 (“Reduced On-Farm Model”), where both DMI and BW were excluded. Evaluation on test datasets either with RC data (n = 103), GF data without additives (n = 478) or GF data only including observations where nitrate, 3-nitrooxypropanol (3-NOP), or a combination of nitrate and 3-NOP were fed to the cows (GF+: n = 295), showed good precision of the 3 models, illustrated by low slope bias both in absolute values (-0.22 to 0.097) and in percentage (0.049 to 4.89) of mean square error (MSE). However, the mean bias (MB) indicated systematic over-prediction and under-prediction of CO2 production when the models were evaluated on the GF and the RC test dataset, respectively. To address this bias, the 3 models were evaluated on a modified test dataset, where the CO2 production (g/d) was adjusted by subtracting (where measurements were obtained by RC) or adding absolute MB (where measurements were obtained by GF) from evaluation of the specific model on RC, GF, and GF+ test datasets. By this modification, the absolute values of MB and MB as percentage of MSE became negligible. In conclusion, the 3 models were precise in predicting CO2 production from lactating dairy cows